Chemical Characterization of Roman and Early Byzantine Glass from Boğazköy/Hattuša and its Vicinity

During investigations in the Hittite capital Hattuša the remains of a small, probably village settlement from late antiquity were discovered at various points in the urban area. A necropolis from this epoch is of particular importance. Finds from it as well as finds purchased in the vicinity by the local museum provided the material for archaeometric analyses of the chemical composition of glass specimens from late antiquity. Several groups can be chemically distinguished and they fit well into the known spectrum of eastern Mediterranean glass production. Given these findings, we may assume that the then relatively remote region of Boğazköy was nonetheless integrated in the transregional network supplying raw materials for glass production.Im Zuge der Erforschung der hethitischen Hauptstadt Hattuša wurden an verschiedenen Stellen des Stadtgebietes Reste einer kleinen, wahrscheinlich dörflichen Siedlung der Spätantike freigelegt. Eine besondere Bedeutung kommt einer Nekropole dieser Epoche zu. Funde aus dieser sowie solche, die durch das lokale Museum aus der unmittelbaren Umgebung angekauft wurden, bilden die Grundlage für naturwissenschaftliche Analysen der chemischen Zusammensetzung spätantiker Gläser. Es können mehrere Gruppen chemisch unterschieden werden, die sich gut in das bekannte Spektrum der ostmediterranen Glasproduktion einfügen. Anhand der Ergebnisse kann vermutet werden, daß die in dieser Zeit relativ abgelegene Region Boğazköy dennoch in die überregionale Versorgung mit Rohmaterialien zur Glasproduktion eingebunden war.Hitit başkenti Hattuşaş’ın farklı yerlerinde sürdürülen araştırmalar sırasında Geç Antik döneme ait, olasılıkla bir köy yerleşiminin kalıntıları ortaya çıkmıştır. Bu döneme ait bir nekropol özellikle anlam kazanmıştır. Gerek sözü edilen kazılar sırasında ortaya çıkan gerekse yerel müze tarafından civardan satın alınan buluntular, Geç Antik dönem camlarının kimyasal analizine temel oluşturmaktadır. Buluntuların, Doğu Akdeniz bölgesinin bilinen cam ürünleri çeşitliliğine uygunluk gösteren, kimyasal açıdan birkaç gruba ayrıldığı görülmüştür. Sonuçlardan yola çıkılarak, o zamanlar merkezi konumda olmayan Boğazköy yöresinin, yine de, cam üretiminde kullanılan hammadde bakımından bölgeler arası bir öneme sahip olduğu düşünülebilir

Swift and Suzaku Observations of the X-Ray Afterglow from the GRB 060105

Results are presented of early X-ray afterglow observations of GRB 060105 by Swift and Suzaku. The bright, long gamma-ray burst GRB 060105 triggered the Swift Burst Alert Telescope (BAT) at 06:49:28 on 5 January 2006. The Suzaku team commenced a pre-planned target of opportunity observation at 19 ks (5.3 hr) after the Swift trigger. Following the prompt emission and successive very steep decay, a shallow decay was observed from T_0+187 s to T_0+1287 s. After an observation gap during T_0 +(1.5-3) ks, an extremely early steep decay was observed in T_0+(4-30) ks. The lightcurve flattened again at T_0+30 ks, and another steep decay followed from T_0+50 ks to the end of observations. Both steep decays exhibited decay indices of 2.3 - 2.4. This very early break, if it is a jet break, is the earliest case among X-ray afterglow observations, suggesting a very narrow jet whose opening angle is well below 1 degree. The unique Suzaku/XIS data allow us to set very tight upper limits on line emission or absorption in this GRB. For the reported pseudo-redshift of z=4.0+/-1.3 the upper limit on the iron line equivalent width is 50 eV.Comment: 8 pages, 5 figures, Accepted for publication in PASJ Suzaku Special Issue (vol. 58

Spectral evolution of GRB 060904A observed with Swift and Suzaku -- Possibility of Inefficient Electron Acceleration

We observed an X-ray afterglow of GRB 060904A with the Swift and Suzaku satellites. We found rapid spectral softening during both the prompt tail phase and the decline phase of an X-ray flare in the BAT and XRT data. The observed spectra were fit by power-law photon indices which rapidly changed from $\Gamma = 1.51^{+0.04}_{-0.03}$ to $\Gamma = 5.30^{+0.69}_{-0.59}$ within a few hundred seconds in the prompt tail. This is one of the steepest X-ray spectra ever observed, making it quite difficult to explain by simple electron acceleration and synchrotron radiation. Then, we applied an alternative spectral fitting using a broken power-law with exponential cutoff (BPEC) model. It is valid to consider the situation that the cutoff energy is equivalent to the synchrotron frequency of the maximum energy electrons in their energy distribution. Since the spectral cutoff appears in the soft X-ray band, we conclude the electron acceleration has been inefficient in the internal shocks of GRB 060904A. These cutoff spectra suddenly disappeared at the transition time from the prompt tail phase to the shallow decay one. After that, typical afterglow spectra with the photon indices of 2.0 are continuously and preciously monitored by both XRT and Suzaku/XIS up to 1 day since the burst trigger time. We could successfully trace the temporal history of two characteristic break energies (peak energy and cutoff energy) and they show the time dependence of $\propto t^{-3} \sim t^{-4}$ while the following afterglow spectra are quite stable. This fact indicates that the emitting material of prompt tail is due to completely different dynamics from the shallow decay component. Therefore we conclude the emission sites of two distinct phenomena obviously differ from each other.Comment: 19 pages, 9 figures, accepted for publication in PASJ (Suzaku 2nd Special Issue

The functional connectome in obsessive-compulsive disorder: resting-state mega-analysis and machine learning classification for the ENIGMA-OCD consortium

Current knowledge about functional connectivity in obsessive-compulsive disorder (OCD) is based on small-scale studies, limiting the generalizability of results. Moreover, the majority of studies have focused only on predefined regions or functional networks rather than connectivity throughout the entire brain. Here, we investigated differences in resting-state functional connectivity between OCD patients and healthy controls (HC) using mega-analysis of data from 1,024 OCD patients and 1,028 HC from 28 independent samples of the ENIGMA-OCD consortium. We assessed group differences in whole-brain functional connectivity at both the regional and network level, and investigated whether functional connectivity could serve as biomarker to identify patient status at the individual level using machine learning analysis. The mega-analyses revealed widespread abnormalities in functional connectivity in OCD, with global hypo-connectivity (Cohen’s d: -0.27 to -0.13) and few hyper-connections, mainly with the thalamus (Cohen’s d: 0.19 to 0.22). Most hypo-connections were located within the sensorimotor network and no fronto-striatal abnormalities were found. Overall, classification performances were poor, with area-under-the-receiver-operating-characteristic curve (AUC) scores ranging between 0.567 and 0.673, with better classification for medicated (AUC=0.702) than unmedicated (AUC=0.608) patients versus healthy controls. These findings provide partial support for existing pathophysiological models of OCD and highlight the important role of the sensorimotor network in OCD. However, resting-state connectivity does not so far provide an accurate biomarker for identifying patients at the individual level

Baseline tumour necrosis factor alpha levels predict the necessity for dose escalation of infliximab therapy in patients with rheumatoid arthritis

Objectives: To investigate the possible role of baseline plasma tumour necrosis factor alpha levels (baseline-TNF) on the clinical response to infliximab in patients with rheumatoid arthritis (RA). Methods: Patients with RA refractory to methotrexate received 3, 6, or 10 mg/kg of infliximab every 8 weeks, in a randomised, double-blind manner: the RISING study. Clinical response (disease activity score in 28 joints based on C-reactive protein or American College of Rheumatology core set) at week 54 and serum infliximab levels were compared in three patient groups with low, intermediate, or high baseline-TNF (TNF-low, TNF-int, or TNF-high). Results: In TNF-low patients, the clinical response to different doses of infliximab was comparable, whereas TNF-int patients exhibited a dose-dependent trend. In contrast, TNF-high patients (approximately 13% of the total patients) had a clinical response to 10 mg/kg significantly better than the response to 3 and 6 mg/kg of infliximab. In TNF-high patients, the median trough serum levels of infliximab were below the detection limit (<0.1 μg/ml) at 3 and 6 mg/kg but were greater than 2 μg/ml at 10 mg/kg, whereas the levels were approximately 1 μg/ml for each dosage group in TNF-low patients. Conclusion: In patients with RA, baseline-TNF is significantly associated with the clinical response to infliximab in patients with a high baseline-TNF. A higher dose of infliximab may be necessary in these patients, whereas lower doses of infliximab are sufficient for those with a low baseline-TNF. Baseline-TNF may be a useful measure for personalising the treatment of RA using infliximab

Brain structural covariance networks in obsessive-compulsive disorder: a graph analysis from the ENIGMA Consortium.

Brain structural covariance networks reflect covariation in morphology of different brain areas and are thought to reflect common trajectories in brain development and maturation. Large-scale investigation of structural covariance networks in obsessive-compulsive disorder (OCD) may provide clues to the pathophysiology of this neurodevelopmental disorder. Using T1-weighted MRI scans acquired from 1616 individuals with OCD and 1463 healthy controls across 37 datasets participating in the ENIGMA-OCD Working Group, we calculated intra-individual brain structural covariance networks (using the bilaterally-averaged values of 33 cortical surface areas, 33 cortical thickness values, and six subcortical volumes), in which edge weights were proportional to the similarity between two brain morphological features in terms of deviation from healthy controls (i.e. z-score transformed). Global networks were characterized using measures of network segregation (clustering and modularity), network integration (global efficiency), and their balance (small-worldness), and their community membership was assessed. Hub profiling of regional networks was undertaken using measures of betweenness, closeness, and eigenvector centrality. Individually calculated network measures were integrated across the 37 datasets using a meta-analytical approach. These network measures were summated across the network density range of K = 0.10-0.25 per participant, and were integrated across the 37 datasets using a meta-analytical approach. Compared with healthy controls, at a global level, the structural covariance networks of OCD showed lower clustering (P &lt; 0.0001), lower modularity (P &lt; 0.0001), and lower small-worldness (P = 0.017). Detection of community membership emphasized lower network segregation in OCD compared to healthy controls. At the regional level, there were lower (rank-transformed) centrality values in OCD for volume of caudate nucleus and thalamus, and surface area of paracentral cortex, indicative of altered distribution of brain hubs. Centrality of cingulate and orbito-frontal as well as other brain areas was associated with OCD illness duration, suggesting greater involvement of these brain areas with illness chronicity. In summary, the findings of this study, the largest brain structural covariance study of OCD to date, point to a less segregated organization of structural covariance networks in OCD, and reorganization of brain hubs. The segregation findings suggest a possible signature of altered brain morphometry in OCD, while the hub findings point to OCD-related alterations in trajectories of brain development and maturation, particularly in cingulate and orbitofrontal regions

A common brain network among state, trait, and pathological anxiety from whole-brain functional connectivity

Anxiety is one of the most common mental states of humans. Although it drives us to avoid frightening situations and to achieve our goals, it may also impose significant suffering and burden if it becomes extreme. Because we experience anxiety in a variety of forms, previous studies investigated neural substrates of anxiety in a variety of ways. These studies revealed that individuals with high state, trait, or pathological anxiety showed altered neural substrates. However, no studies have directly investigated whether the different dimensions of anxiety share a common neural substrate, despite its theoretical and practical importance. Here, we investigated a brain network of anxiety shared by different dimensions of anxiety in a unified analytical framework using functional magnetic resonance imaging (fMRI). We analyzed different datasets in a single scale, which was defined by an anxiety-related brain network derived from whole brain. We first conducted the anxiety provocation task with healthy participants who tended to feel anxiety related to obsessive-compulsive disorder (OCD) in their daily life. We found a common state anxiety brain network across participants (1585 trials obtained from 10 participants). Then, using the resting-state fMRI in combination with the participants' behavioral trait anxiety scale scores (879 participants from the Human Connectome Project), we demonstrated that trait anxiety shared the same brain network as state anxiety. Furthermore, the brain network between common to state and trait anxiety could detect patients with OCD, which is characterized by pathological anxiety-driven behaviors (174 participants from multi-site datasets). Our findings provide direct evidence that different dimensions of anxiety have a substantial biological inter-relationship. Our results also provide a biologically defined dimension of anxiety, which may promote further investigation of various human characteristics, including psychiatric disorders, from the perspective of anxiety

A neural marker of obsessive-compulsive disorder from whole-brain functional connectivity

Obsessive-compulsive disorder (OCD) is a common psychiatric disorder with a lifetime prevalence of 2-3 percent. Recently, brain activity in the resting state is gathering attention as a new means of exploring altered functional connectivity in psychiatric disorders. Although previous resting-state functional magnetic resonance imaging studies investigated neurobiological abnormalities of patients with OCD, there are concerns that should be addressed. One concern is the validity of the hypothesis employed. Most studies used seed-based analysis of the fronto-striatal circuit, despite the potential for abnormalities in other regions. A hypothesis-free study is a promising approach in such a case, while it requires researchers to handle a dataset with large dimensions. Another concern is the reliability of biomarkers derived from a single dataset, which may be influenced by cohort-specific features. Here, by employing a recently developed machine-learning algorithm to avoid these concerns, we identified the first OCD biomarker that is generalized to an external dataset. We also demonstrated that the functional connectivities that contributed to the classification were widely distributed rather than locally constrained. Our generalizable classifier has the potential not only to deepen our understanding of the abnormal neural substrates of OCD but also to find use in clinical applications.Comment: 47 pages, 3 figure